hits
Generic Description
Produce authority and hub scores.
Simple example:
CALL nexyron.hits()
Centrality procedures rank nodes by structural importance. They are useful for influence, dependency, bottleneck, and exposure analysis, but each metric encodes a different meaning of importance.
Consumer-Level Explanation
Use hits when produce authority and hub scores is the graph-analysis or operational question you actually need to answer. Keep the call explicit because its YIELD columns, row grain, and required runtime state determine how the rest of the Cypher pipeline can safely compose it. Do not treat centrality scores as interchangeable: degree measures direct volume, PageRank and eigenvector-style scores reward endorsement by important neighbors, betweenness finds bridge nodes, and closeness/harmonic scores emphasize reachability.
Conceptual Explanation
hits should be read as one named procedure contract in the broader Nexyron Cypher surface. The procedure call is not only a syntax hook: it defines what runtime state, projection, registry entry, or graph algorithm is being asked to operate, and it determines which output columns downstream YIELD, WITH, and RETURN stages can safely use.
More Detailed Explanation
HITS differs from PageRank because it explicitly separates good destinations from good referrers
In practical queries, start by deciding the row grain you want after the call: one row per node, one row per path, one row per registry object, one row per artifact, or one row per summary. Then keep that grain explicit with YIELD and named projections. That is the difference between a useful planner-facing example and a vague call that downstream tooling cannot safely compose. For contract-driven procedures, the executable examples on these pages intentionally inspect procedure metadata unless the required named artifacts are created in the same example.
How It Differs From Nearby Algorithms
HITS differs from PageRank because it explicitly separates good destinations from good referrers.
Advanced Example
This example yields named columns from hits and returns a bounded result shape that downstream planner tooling can compose without guessing column names or row grain.
CALL nexyron.hits() YIELD node_id, authority, hub
RETURN node_id, authority, hub
LIMIT 10
Real Use Cases
- content authority vs curator hub analysis
- bipartite or citation-like graphs
- distinguishing sources from aggregators
- compare algorithm output with domain labels or time windows before operationalizing it
- feed graph-analytic scores into ranked reports, feature contracts, or investigation queues only after checking the modeling assumptions
Real Limitations And Tradeoffs
- authority and hub are easy to misuse if the graph is not semantically directional
- algorithm output reflects the projected graph, not an abstract real-world network outside the data model
- nearby algorithms can answer different questions even when their output columns look similar